Incremental Modeling of Supply Chain to Improve Performance Measures

Szczepan Górtowski , Elżbieta Lewańska

Abstract

Supply chain modeling is one of the key tools to improve its performance measures. This research follows the principles of Design Science Research (DSR). The paper presents the concept of incremental modeling, which helps quick adaptation of the suply chain model. This method uses Data Science methods and Big Data. Evaluation of the method will be conducted on the franchise network. Hence, new performance measures classification that contains measures specific to the needs of the franchise network, has been developed. In particular measures that allow assessing the level of cooperation around conflicting goals of franchise network participants are included. The results will improve the cooperation of entities within franchise networks.
Author Szczepan Górtowski (WIiGE / KIE)
Szczepan Górtowski,,
- Department of Information Systems
, Elżbieta Lewańska (WIiGE / KIE)
Elżbieta Lewańska,,
- Department of Information Systems
Pages637-648
Publication size in sheets0.55
Book Abramowicz Witold, Corchuelo Rafael (eds.): Business Information Systems Workshops: BIS 2019 International Workshops Seville, Spain, June 26-28, 2019, Revised Papers, Lecture Notes in Business Information Processing, vol. 373, 2019, Springer, ISBN 978-3-030-36690-2, [978-3-030-36691-9], 698 p., DOI:10.1007/978-3-030-36691-9
Keywords in Polishłańcuch dostaw, mierniki efektywności, projektowanie łańcucha dostaw, modelowanie łańcucha dostaw, Big Data, Data Science, franczyza, retail
Keywords in EnglishSupply chain, Performance measures, Supply chain design, Supply chain modeling, Big data, Data Science, Franchising, Retail
ASJC Classification1802 Information Systems and Management; 2611 Modelling and Simulation; 1710 Information Systems; 1403 Business and International Management; 2207 Control and Systems Engineering; 1404 Management Information Systems
DOIDOI:10.1007/978-3-030-36691-9_53
Languageen angielski
Score (nominal)70
Score sourceconferenceList
ScoreMinisterial score = 70.0, 22-04-2020, ChapterFromConference
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